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New global findings on capturing value from
flow optimisation & smart logistics
Nick Gazzard CEO Incept
© Inception Consulting Ltd 2016
Incept specialises in “end-to-end” multi-actor value network analysis
using industry best practise research expertise and extensive global
experienceIndustry groups and NGO’sAcademic partners & publications
“Enabling new opportunities to enhance performance in
value networks”
"Value Networks aid our understanding and ability to
address key issues and opportunities in our business“
Wal Mart
Recent client engagements include
© Inception Consulting Ltd 2016
Sources: Prof Martin Christopher 1998, Images – Maersk & Globaia.org
Trading off manufacturing and consumer delivery cost
ContainerisationGrowth in global trade
What shaped global freight networks?
What now?
Sources: Cerasis,, Cruijssen,F. Argus DPD Microzoning Rotterdam 2015, FT, Forrester, Garry White / Telegraph April 2014 Oct 2014 Times Jan 2014, Roland Berger, Stats SA 2016, DBW April 28th 2016, Wall St Journal 2014, ONS UK 2014, IGD Supply chain analysis 2016 UK Cencsus
Cities only cover
2% of the earth’s
surface but
consume 75% of
its resources
Urbanisation & eCommercetransforming consumer behaviour Last mile activity = 65% of retail costs
Delivery frequency up = drop size down + rising inventory = higher costs
Growing product ranges increase the number of slow moving SKU’s
Activities like layer pallet picking are driving dramatic increases in costs
Discount & on-line = big challenge for traditional retail
Sector investment prospects downgraded
Sector economics in South Africa are becoming brutal
Q1 Sales + 28% to $ 29 BnAmazon fresh launches in
UK with 130,000 SKUs 1 Hour delivery slots 7am –11pm + same day delivery
for orders by 1pm
For c. 2.9m customers
Sources: PI Montreuil / Ballot, UPS, Bayer, Google, BBC Rolls Royce 2014, Starship technologies, Economist, Incept reverse Pharma model 2016
Disruptive business models technology & AI
Step change scale efficiencies
Adaptive urban logistics
Modular manufacturing
Sustainable “eco-nomics”
Prosumer (demand) driven “omni-channel” networks
Transformed product and channel economics
Compelling needs to reduce costs & time taken for agility
Sense & respond network Push driven chain
What will drive future global networks?
“So what” do we do?
Sources: Graphic Head Heart + Brain, Jeffrey Pfeffer Professor of Organizational Behavior Stanford University Graduate School of Business, Robert I. Sutton, professor of management science and engineering at Stanford, German Institute
of management 2008, Bloomberg data, Capital IQ, Booz & Co 2015
Casual benchmarking leads to adopting practices of
successful organizations without understanding the
circumstances of the success Repeating what worked in the past without
examining whether the context is the same
Following deeply held yet unexamined ideologies
Weak innovation culture and low R&D spend
With economics likely to remain tough
Evolving marketing models & changing consumer behaviour are driving costs up
As success is increasingly determined by agile competing value chains and networks
“Sitting it out” is not an option
So reducing costs is critical but costs are rising - so what is going wrong?
Averaged costing (in)accurate to 3 decimals misses opportunities
“People with a high tolerance for ambiguity typically do not become
financial managers”Robert S. Kaplan
SOX & GAAP Drive “compliance”
But costs are a function of ever more complex mixes of activity products & flows
As complexity rises higher level cost allocation neither reflects or predicts costs accurately
So true cost drivers & opportunities can be hidden….. or worse
The BIG opportunities are mostly inside the averages
Total E2E cost change•1 Delivery per week = €64•5 Per week = €85 +32%
Vs Retail benefit -14%
SKU
Co
st pe
r case
Cumulative SKU % of volume
Slow movers
Fast movers
Medium movers
No
of flo
ws 1
6,0
00
-0
Average # of pallets 1 – 34 (L to R)
• Normal pallet = €38-65
• Layer pallet = € 114
• Jumble pallet = €165
• Normal cost €0.68
• Customised €1.81
Product customisation
Layer pallet study Case study
Unit load optimisationTransport optimisation
“Using NVM the companies put together a detailed view
of supply chain costs from point of manufacture
through to the retail DC, the tool showed very clearly
there are substantial savings to be made in the total
supply chain I don’t think we realised previously how
big these savings were”
Trevor Currie Group Logistics Director
SPAR South Africa
SPAR Cost and flow optimisation for 15,000 SKUs
9
SKU
Store sto
ck level
Flow optimisation SKU Range & flow groups
SKU
Co
st per case
Cumulative % of volume
Size of the prize : SKU flow optimisation
Fast moversE2E display
pallets & single SKU unit loads
Medium movers
Automation & multi SKU unit
loads
Slow moversSub-case picking to container
Display loads drive store handling and transport efficiency
Item picking drives down in-store inventory and space
Modular loads drive store handling and > roll cage efficiency
> -30%
0 10 20 30 40 50 60 70 80 90 100
0
50
100
150
200
250
300
350
OR
DE
R S
IZE
BY
SK
U
TOP 100 SKUS RANKED BY ORDER SIZE
Top 100 SKUs Potential to order on display pallets
Avg SKU cases per delivery Order on Pallet Order on Qtr pallet Order on Half pallet
Up to 50% of top 100 SKUs could be Delivered on display pallets > -40% > -50%
(representative data)
Size of the prize : E2E Collaborative cost modelling group
Source: CHEP CAP E2E Group
The group developed an NVM model for 180 scenarios covering 7 product categories, 5 routes to market (RTM), 3 operational models, 2 retailer models, 3 delivery frequencies & 2 order volumes
Some open collaboration
scenarios show 50 % savings Vs
current costs
Size of the prize : E2E Collaborative group roadmap
• xx
Online channels are complex and hard to cost
13
Source: CHEP CAP E2E NVM Multi-channel analysis 2015
Own label long grain rice 1kg 1 kg
Tomato soup 300g 300g
Classy pesto 190g
Cola 2-litre 2 Litre
Jamaica Ginger cake 290g
Own label olive oil 500ml 500ml
Own label baked beans 420g 420g
O Sole mio Bolognese sauce 500g 500g
Aquamint 100ml 100ml
Redux herbal bath 500ml 500ml
Own label toilet tissue 4-pack 4-pack
ShreddyFlakes 750g 750g
Students Super Noodles any flavour 1OOg 1OOg
Tutley tea bags 160s 500g
After Ates Mints 300g carton 300g
Chadbury Dairy Milk 200g 200g
Australian red wine 75cl cheapest on display 75cl
We modelled a basket of 17 products through the
14 channels
To model this drives >10,000 SKU activities X 330 input variables
equivalent to 3,300,000 individual cost rates
Analysis shows a really significant channel cost gradient
Growth for multi-channel retailers is coming in channels costing up to 4 x hard discount
Pu
sh d
riven ch
ainSen
se & resp
on
d n
etwo
rk
Source: CHEP CAP E2E NVM Multi-channel analysis 2015, Internet World Stats 2016
SA Online sales growth c. 25%
€1.79 per Eq case
€9.83 per Eq case
Size of the prize : Networks & modular loads
Over 149 activities in 34 locations for >3,000 RTMs & >160,000 specific cost / CO2e rates
The average cost per case for the current scenario was €1.39
Lowest cost using “open” supply chains & modular loads was €0.55
Saving €0.84 or 60% Vs the base
Sources: Modulushca WP 5.2 cost analysis 2014
The scenarios covered network & process
options from 1:1 traditional operations
to shared networks using modular loads
S1
S2
S3
S4
S5
S6
0 0.050.10.150.20.250.30.350.40.450.50.550.60.650.70.750.80.850.90.951 1.051.11.151.21.251.31.351.41.451.51.551.61.65
0.50
0.52
0.59
0.51
0.61
0.42
1.13
1.13
1.46
1.38
1.52
1.32M-Box
Pallet
Cost per case by scenario and equipment type
Excluding packaging
Sources: Damage in FMCG Supply chain Wood, G. Pira International Carton user group 2002. Graphic Incept NVM, Netto – Dematic HSS 2015
Are we ready for a modular future?
Physical Internet offers potential savings of
-22% in total km
+15% efficiency
+20% load factor
-50% CO2 (intermodal)
Up to 60% reduction in logistics costs by using modular unit loads
nbox
Dator’s second law of the future states “Any useful
idea about the future should appear to be
ridiculous”………
Sources: PI Montreuil / Ballot, UPS, Bayer, Incept nBox, James Allen Dator Hawaii Research Center for Futures, ES3 2015, DHL Supply Chain warehouse Unna DE robot called EffiBOT from Effidence 2016
Emerging and future modular concepts
Diving into the future - Modular unit load handing trials
Will modularity & connections work?
YES
Can fork lift & clamp trucks handle it?
YES
Empty
120Kg load
Loaded box
Layer dolly
Empty boxes collapse & lock
together & could be mixed
with full
Side can open for inspection
or in-store display
Operation could be faster but opening unpacking & collapsing took 30 secs
A single connected box held 90 kg & another was handled by clamp truck
The layer connector lifted a 120 kg load
The boxes travelled 2,753 km in 5 countries with no damage in the trials
nbox
With potential to save up to 60% of costsWhat are we waiting for………….?